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Bayesian Inference

Bayesian Inference is a methodology that employs Bayes Rule to estimate parameters (and their full posterior).

Papers

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Showing 1571–1580 of 2226 papers

TitleStatusHype
Deep learning-based prediction of kinetic parameters from myocardial perfusion MRI—0
Bayesian Inference with Generative Adversarial Network Priors—0
Bayesian Inference Gaussian Process Multiproxy Alignment of Continuous Signals (BIGMACS): Applications for PaleoceanographyCode0
Subspace Inference for Bayesian Deep LearningCode0
SubTSBR to tackle high noise and outliers for data-driven discovery of differential equations—0
A General Framework for Uncertainty Estimation in Deep LearningCode0
Stochastic gradient Markov chain Monte CarloCode0
Concentration of the matrix-valued minimum mean-square error in optimal Bayesian inference—0
Bayesian Synthesis of Probabilistic Programs for Automatic Data Modeling—0
Etalumis: Bringing Probabilistic Programming to Scientific Simulators at ScaleCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1F-SWAAccuracy83.61—Unverified
2F-SWAGAccuracy80.93—Unverified